1. Field of the Invention
The present invention relates to the computerized quantitative analysis of digital chest radiographs, and in particular to a method and system for detection of posterior ribs and pneumothorax in digital chest radiographs.
2. Discussion of the Background
It is commonly believed that the rib structure in chest radiographs provides a frame of reference for quantitative analysis of digital chest images, such as the analysis of temporal changes between successive digital chest images. For example, in the case of a lung cancer that develops during the interval between two chest X-ray examinations, a temporal subtraction technique has been used to improve detectability, provided that the rib structures in the two images may be matched by converting the locations of ribs in one image to those of another, as suggested by Kinsey et al "Application of Digital Image Change Detection to Diagnosis and Follow-up of Cancer Involving Lungs," Proceedings of SPIE 70, 99-112 (1975).
It has also been shown that many false-positives occur at ribs and rib crossings in computerized detection of lung nodules in a single frontal chest radiograph. M. L. Giger et al "Pulmonary Nodules: Computer-Aided Detection in Digital Chest Images," RadioGraphics 10, 41-51 (1990), and Yoshimura et al "Analysis of Computer-Reported False-Positive Detections of Lung Nodules in Digital Chest Radiography," Med. Phys. 17, 524 (P) (1990). For quantitative analysis of lung textures related to interstitial diseases, many regions-of-interest (ROIs) need to be selected automatically in the intercostal spaces. Thus, accurate knowledge of rib locations is essential for the development of a reliable method for automated selection of ROIs.
In the prior art, various methods have been developed for automated rib detection. Generally, these methods have attempted to detect local rib edges while applying some anatomic knowledge to construct the rib structure. However, these methods are still far from being ready for practical use on clinical chest images, and some difficulties in automated rib detection remain. For example, chest images contain radiographic noise and also many confusing edges due to blood vessels, bronchi, lung texture, lesions and artifacts. In addition, rib contrast is commonly low, and rib edges are often ill-defined because of poor image quality. Accordingly, the signal-to-noise ratio of rib structures is generally low.
Similarly, accurate knowledge of rib locations is useful for development of automated techniques for the detection of pneumothorax. Pneumothorax is a condition caused by an accumulation of air or gas in the pleural cavity, which occurs as a result of disease or injury. Radiographic detection of pneumothorax is commonly based on a subtle, fine curved-line pattern in the apical lung region, a dark pleural air space against the chest wall due to increased transparency, and a lack of lung structure between the rib cage and the pneumothorax pattern. Although pneumothoraces are clinically important abnormalities, it is difficult to detect them, in part because there is overlap between the pneumothoraces and the ribs and clavicle. Prior art techniques have been used to enhance the pneumothorax pattern by use of digital processing of chest images. However, no attempt has been made to detect pneumothorax automatically by means of a computer. Computerized, automated detection of subtle pneumothorax patterns would be helpful for the diagnosis made by radiologists in that they will be alerted to a potential subtle lesion.